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Field
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matter physics, biomedical/material engineering or a related discipline. You have a strong background in data analysis and image processing. You enjoy working in interdisciplinary and international teams
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to study translational aspects of cancer (single-cell sequencing of immune cells, organoid co-cultures, cellular engineering via CRISPR/Cas9 technology, in vivo imaging, advanced animal models of allo-SCT
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closed-loop control. The technology, developed through detailed computer simulations, will be validated with preclinical experiments. The candidate will be part of a multidisciplinary team working towards
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(SOTA) Federated Learning algorithms. This includes running a few pre-processing pipelines. Develop SOTA algorithms in Robustness against data and model poisoning attacks. Develop SOTA algorithms in
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the research areas of Infection Medicine and Microbiology, Immunology, Oncology, Neurosciences, Pharmacology/Cardiology/Vascular Medicine, Imaging Technology and Biomedical Engineering, amongst others. A large
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experimental use of organoid models (provided by a partner institute), including adaptation for biophysical assays and imaging Experimental investigations using atomic force microscopy (AFM), including force